Update README.md

README.md

@@ -24,7 +24,7 @@ license: apache-2.0
 
 ## Model description 
 
-DocExplainer is a an approach to Visual Document Question Answering with bounding box localization.  
+DocExplainer is a an approach to Visual Document Question Answering (Document VQA) with bounding box localization.  
 Unlike standard VLMs that only provide text-based answers, DocExplainer adds **visual evidence through bounding boxes**, making model predictions more interpretable.  
 It is designed as a **plug-and-play module** to be combined with existing Vision-Language Models (VLMs), decoupling answer generation from spatial grounding.  
 
@@ -162,22 +162,12 @@ Example Output:
 
 
 ## Performance 
-Evaluated on [BoundingDocs v2.0](https://huggingface.co/datasets/letxbe/BoundingDocs) dataset: 
-### Full DocExplainer Pipeline 
-
-| VLM Model       | ANLS ↑| IoU ↑ |
-| --------------- | ----- | ----- | 
-| SmolVLM2-2.2b   | 0.572 | 0.175 |
-| qwen2.5-vl-7b   | 0.689 | 0.188 |
-
-     
-### VLM-only Baseline (for comparison)
-| VLM Model       | ANLS ↑| IoU ↑ |
-| --------------- | ----- | ----- | 
-| SmolVLM2-2.2b   | 0.561 | 0.011 |
-| qwen2.5-vl-7b   | 0.720 | 0.038 |
-| Claude Sonnet 4 | 0.737 | 0.031 |
 
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/66436107bfa436269e92b10a/53foSyYSG55GgP1yGCyvn.png)
+
+Document VQA performance of different models and prompting strategies on the BoundingDocs v2.0 dataset. <br>
+Smol stands for SmolVLM-2.2B, Qwen stands for Qwen2-VL-7B, and D.E. stands for DocExplainerV0.  <br>
+The best value is shown in **bold**, the second-best value is <ins>underlined</ins>.
 
 ## Limitations
 - **Prototype only**: Intended as a first approach, not a production-ready solution.